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Prediction of Surfactants' Properties using Multiscale Molecular Modeling Tools A Review

By: Language: Inglés Publication details: nov./dic. 2012Description: 13 p. ; 969-982 In: Summary: Traducción del resúmen del autor: During one of the existing Enhanced Oil Recovery (EOR) procedures, a mixture of Alkaline/Surfactant/Polymer (ASP) is injected into wells in order to move the trapped oil from the reservoir to the wellbores. The conception and/or the tuning of new ASP combinations, structures of surfactants and/or mixtures of surfactants is of primary interest to improve the efficiency of a such procedure. Molecular modeling tools can be used to understand microscopic effects, predict surfactants' properties and finally to optimize structures and mixtures of surfactants. We propose in this article a review of the literature on the ability of molecular simulation techniques such as Molecular Dynamics (MD), Monte Carlo (MC) simulations, Dissipative Particle Dynamics (DPD) and upper scale modeling methods such as Quantitative Structure-Property Relationship (QSPR) approaches to predict thermo-physical and structural properties of surfactants.
Item type: Artículo de Revista
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Biblioteca Alejandro Angel Bulgheroni Not for loan 200059791

Traducción del resúmen del autor: During one of the existing Enhanced Oil Recovery (EOR) procedures, a mixture of Alkaline/Surfactant/Polymer (ASP) is injected into wells in order to move the trapped oil from the reservoir to the wellbores. The conception and/or the tuning of new ASP combinations, structures of surfactants and/or mixtures of surfactants is of primary interest to improve the efficiency of a such procedure. Molecular modeling tools can be used to understand microscopic effects, predict surfactants' properties and finally to optimize structures and mixtures of surfactants. We propose in this article a review of the literature on the ability of molecular simulation techniques such as Molecular Dynamics (MD), Monte Carlo (MC) simulations, Dissipative Particle Dynamics (DPD) and upper scale modeling methods such as Quantitative Structure-Property Relationship (QSPR) approaches to predict thermo-physical and structural properties of surfactants.

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